The Extended Sub-look Analysis In Polarimetric SAR Data For Ship Detection

The monitoring of maritime areas with remote sensing is essential for security reasons and also for the conservation of environment. The synthetic aperture radar (SAR) can play an important role in this matter by considering the possibility of acquiring high-resolution images at nighttime and under cloud cover. Recently, the new approaches based on the sub-look analysis for preserving the information of point targets (such as ship) in the spectrum of the SAR image have been proposed. In the sub-look analysis, the correlation of the ships in two sub-look images is preserved. Based on this property, in this paper first by using the second order statistics of polarimetric SAR data and the information of different polarization bases, the complex correlation between sub-look images is calculated. Then, using a criterion dependent on each of the four polarimetric channels and all polarization bases, the identification of ships from the sea is carried out. The proposed ship detection method is implemented on RADARSAT-2 image at C-band of Sanfrancisco area. The experimental results demonstrate that the method can discriminate the ships from background (sea clutter) with optimal contrast and desirable accuracy. The accuracy of the proposed method is about 19 and 17 percent better than other polarimetric methods and about 30, 2 and 35 percent better than the methods based on the spectral analysis.